tslm
is used to fit linear models to time series including trend and
seasonality components.
tslm(formula, data, subset, lambda = NULL, biasadj = FALSE, ...)
formula  an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted. 

data  an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which lm is called. 
subset  an optional subset containing rows of data to keep. For best
results, pass a logical vector of rows to keep. Also supports

lambda  BoxCox transformation parameter. Ignored if NULL. Otherwise, data are transformed via a BoxCox transformation. 
biasadj  Use adjusted backtransformed mean for BoxCox transformations. If TRUE, point forecasts and fitted values are mean forecast. Otherwise, these points can be considered the median of the forecast densities. 
...  Other arguments passed to 
Returns an object of class "lm".
tslm
is largely a wrapper for lm()
except that
it allows variables "trend" and "season" which are created on the fly from
the time series characteristics of the data. The variable "trend" is a
simple time trend and "season" is a factor indicating the season (e.g., the
month or the quarter depending on the frequency of the data).
y < ts(rnorm(120,0,3) + 1:120 + 20*sin(2*pi*(1:120)/12), frequency=12) fit < tslm(y ~ trend + season) plot(forecast(fit, h=20))